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案例研究 - 一家公司正在使用 Amazon SageMaker 构建基于 Web 的 AI 应用程序。该应用程序将提供以下功能和特性：机器学习实验、训练、中央模型注册表、模型部署和模型监控。应用程序必须确保在机器学习生命周期中安全且隔离地使用训练数据。训练数据存储在 Amazon S3 中。该公司需要使用中央模型注册表来管理应用程序中不同版本的模型。哪种操作能够以最少的运营开销满足此要求？

英文：A company is building a web-based AI application by using Amazon SageMaker. The application will provide the following capabilities and features: ML experimentation, training, a central model registry, model deployment, and model monitoring.

The application must ensure secure and isolated use of training data during the ML lifecycle. The training data is stored in Amazon S3.

The company needs to use the central model registry to manage different versions of models in the application. Which action will meet this requirement with the LEAST operational overhead?

案例研究 - 一家公司正在使用 Amazon SageMaker 构建基于 Web 的 AI 应用程序。该应用程序将提供以下功能和特性：机器学习实验、训练、中央模型注册表、模型部署和模型监控。应用程序必须确保在机器学习生命周期中安全且隔离地使用训练数据。训练数据存储在 Amazon S3 中。该公司正在尝试连续培训工作。公司如何才能最大限度地缩短这些工作的基础设施启动时间？

英文：

A company is building a web-based AI application by using Amazon SageMaker. The application will provide the following capabilities and features: ML experimentation, training, a central model registry, model deployment, and model monitoring.

The application must ensure secure and isolated use of training data during the ML lifecycle. The training data is stored in Amazon S3.

The company is experimenting with consecutive training jobs.

How can the company MINIMIZE infrastructure startup times for these jobs?

案例研究 - 一家公司正在使用 Amazon SageMaker 构建基于 Web 的 AI 应用程序。该应用程序将提供以下功能和特性：机器学习实验、训练、中央模型注册表、模型部署和模型监控。应用程序必须确保在机器学习生命周期中安全且隔离地使用训练数据。训练数据存储在 Amazon S3 中。公司必须实施基于手动审批的工作流程，以确保只有经过批准的模型才能部署到生产端点。哪种解决方案可以满足这个要求？

英文：

The application must ensure secure and isolated use of training data during the ML lifecycle. The training data is stored in Amazon S3.

The company must implement a manual approval-based workflow to ensure that only approved models can be deployed to production endpoints.

Which solution will meet this requirement?

案例研究 - 一家公司正在使用 Amazon SageMaker 构建基于 Web 的 AI 应用程序。该应用程序将提供以下功能和特性：机器学习实验、训练、中央模型注册表、模型部署和模型监控。应用程序必须确保在机器学习生命周期中安全且隔离地使用训练数据。训练数据存储在 Amazon S3 中。该公司需要运行按需工作流程来监控从应用程序部署到实时端点的模型的偏差漂移。哪一个动作可以满足这个要求？

英文：

The application must ensure secure and isolated use of training data during the ML lifecycle. The training data is stored in Amazon S3.

The company needs to run an on-demand workflow to monitor bias drift for models that are deployed to real-time endpoints from the application.

Which action will meet this requirement?

案例研究 - 一名 ML 工程师正在 AWS 上开发欺诈检测模型。训练数据集包括来自本地 MySQL 数据库的交易日志、客户资料和表。交易日志和客户资料存储在 AmazonS3 中。数据集存在类别不平衡，这会影响模型算法的学习。此外，许多功能具有相互依赖性。该算法并未捕获数据中所有所需的底层模式。哪种 AWS 服务或功能可以聚合来自各种数据源的数据？英文：An ML engineer is developing a fraud detection model on AWS. The training dataset includes transaction logs, customer profiles, and tables from an on-premises MySQL database. The transaction logs and customer profiles are Stored in Amazon S3. The dataset has a class imbalance that affects the learning of the model's algorithm. Additionally, many of the features have interdependencies. The algorithm is not capturing all the desired underlying patterns in the data. Which AWS service or feature can aggregate the data from the various data sources?

案例研究 - 一位 ML 工程师正在 AWS 上开发欺诈检测模型。训练数据集包括事务日志、客户资料和本地MySQL 数据库中的表。交易日志和客户资料存储在 Amazon S3 中。数据集存在类不平衡，影响模型算法的学习。此外，许多功能具有相互依赖性。该算法并未捕获数据中所有所需的基础模式。聚合数据后，机器学习工程师必须实施一种解决方案来自动检测数据中的异常情况并可视化结果。哪种解决方案可以满足这些要求？ An ML engineer is developing a fraud detection model on AWS. The training dataset includes transaction logs, customer profiles, and tables from an on-premises MySQL database. The transaction logs and customer profiles are stored in Amazon S3. The dataset has a class imbalance that affects the learning of the model's algorithm. Additionally, many of the features have interdependencies.The algorithm is not capturing all the desired underlying patterns in the data. After the data is aggregated, the ML engineer must implement a solution to automatically detect anomalies in the data and to visualize the Result. Which solution will meet these requirements?

案例研究 - 一位 ML 工程师正在 AWS 上开发欺诈检测模型。训练数据集包括事务日志、客户资料和本地MySQL 数据库中的表。交易日志和客户资料存储在 Amazon S3 中。数据集存在类不平衡，影响模型算法的学习。此外，许多功能具有相互依赖性。该算法并未捕获数据中所有所需的基础模式。训练数据集包括分类数据和数值数据。机器学习工程师必须准备训练数据集，以最大限度地提高模型的准确性。哪种操作能够以最少的运营开销满足此要求？ An ML engineer is developing a fraud detection model on AWS. The training dataset includes transaction logs, customer profiles, and tables from an on-premises MySQL database. The transaction logs and customer profiles are stored in Amazon S3. The dataset has a class imbalance that affects the learning of the model's algorithm. Additionally, many of the features have interdependencies. The algorithm is not capturing all the desired underlying patterns in the data. The training dataset includes categorical data and numerical data. The ML engineer must prepare the training dataset to maximize the accuracy of the model. Which action will meet this requirement with the LEAST operational overhead?

案例研究 - 一位 ML 工程师正在 AWS 上开发欺诈检测模型。训练数据集包括事务日志、客户资料和本地MySQL 数据库中的表。交易日志和客户资料存储在 Amazon S3 中。数据集存在类不平衡，影响模型算法的学习。此外，许多功能具有相互依赖性。该算法并未捕获数据中所有所需的基础模式。在机器学习工程师训练模型之前，机器学习工程师必须解决数据不平衡的问题。哪种解决方案能够以最少的操作工作量满足此要求？ An ML engineer is developing a fraud detection model on AWS. The training dataset includes transaction logs, customer profiles, and tables from an on-premises MySQL database. The transaction logs and customer profiles are stored in Amazon S3. The dataset has a class imbalance that affects the learning of the model's algorithm. Additionally, many of the features have interdependencies. The algorithm is not capturing all the desired underlying patterns in the data. Before the ML engineer trains the model, the ML engineer must resolve the issue of the imbalanced data. Which solution will meet this requirement with the LEAST operational effort?

案例研究 - 一位 ML 工程师正在 AWS 上开发欺诈检测模型。训练数据集包括事务日志、客户资料和本地MySQL 数据库中的表。交易日志和客户资料存储在 Amazon S3 中。数据集存在类不平衡，影响模型算法的学习。此外，许多功能具有相互依赖性。该算法并未捕获数据中所有所需的基础模式。 ML 工程师需要使用 Amazon SageMaker 内置算法来训练模型。机器学习工程师应该使用哪种算法来满足此要求？ An ML engineer is developing a fraud detection model on AWS. The training dataset includes transaction logs, customer profiles, and tables from an on-premises MySQL database. The transaction logs and customer profiles are stored in Amazon S3. The dataset has a class imbalance that affects the learning of the model's algorithm. Additionally, many of the features have interdependencies. The algorithm is not capturing all the desired underlying patterns in the data. The ML engineer needs to use an Amazon SageMaker built-in algorithm to train the model. Which algorithm should the ML engineer use to meet this requirement ?

一家公司在生产中部署了XGBoost 预测模型来预测客户是否可能取消订阅。该公司使用 Amazon SageMaker Model Monitor 来检测F1 分数的偏差。在模型质量的基线分析过程中，公司记录了 F1 分数的阈值。几个月没有变化后，模型的 F1 分数显着下降。 F1 分数降低的原因可能是什么？

英文：A company has deployed an XGBoost prediction model in production to predict if a customer is likely to cancel a subscription.

The company uses Amazon SageMaker Model Monitor to detect deviations in the F1 score.

During a baseline analysis of model quality, the company recorded a threshold for the F1 score. After several months of no change, the model's F1 score decreases significantly. What could be the reason for the reduced F1 score?

一家公司拥有一支数据科学家团队，他们使用 Amazon SageMaker 笔记本实例来测试 ML 模型。当数据科学家需要新权限时，公司会将权限附加到在创建 SageMaker 笔记本实例期间创建的每个单独角色。公司需要对团队的权限进行集中管理。哪种解决方案可以满足这个要求？A company has a team of data scientists who use Amazon SageMaker notebook instances to test ML models. When the data scientists need new permissions, the company attaches the permissions to each individual role that was created during the creation of the SageMaker notebook instance. The company needs to centralize management of the team's permissions.Which solution will meet this requirement?

机器学习工程师需要使用机器学习模型来预测特定位置的公寓价格。机器学习工程师应该使用哪个指标来评估模型的性能？英文：An ML engineer needs to use an ML model to predict the price of apartments in a specific location. Which metric should the ML engineer use to evaluate the model's performance?

机器学习工程师使用随机梯度下降(SGD) 训练了神经网络。神经网络在测试集上表现不佳。训练损失和验证损失的值仍然很高，并显示出振荡模式。在重复相同的循环之前，这些值会在几个时期内减小，然后在几个时期内增加。机器学习工程师应该如何改进训练过程？ An ML engineer has trained a neural network by using stochastic gradient descent (SGD). The neural network performs poorly on the test set. The values for training loss and validation loss remain high and show an oscillating pattern. The values decrease for a few epochs and then Increase for a few epochs before repeating the same cycle. What should the ML engineer do to improve the training process?

ML 工程师需要处理数千个现有 CSV 对象和上传的新 CSV 对象。CSV 对象存储在中央 Amazon S3 存储桶中，并具有相同的列数。其中一列是交易日期。 ML 工程师必须根据交易日期查询数据。哪种解决方案能够以最少的运营开销满足这些要求？ An ML engineer needs to process thousands of existing CSV objects and new CSV objects that are uploaded. The CSV objects are stored in a Central Amazon S3 bucket and have the same number of columns. One of the columns is a transaction date. The ML engineer must query the data based on the transaction date. Which solution will meet these requirements with the LEAST operational overhead?

一家公司拥有庞大的非结构化数据集。该数据集包含多个关键属性的许多重复记录。 AWS 上的哪种解决方案可以使用最少的代码开发来检测数据集中的重复项？英文 A company has a large, unstructured dataset. The dataset includes many duplicate records across several key attributes. Which solution on AWS will detect duplicates in the dataset with the LEAST code development?

一家公司需要在 Amazon EC2 实例上运行批量数据处理作业。该作业将在周末运行，需要 90 分钟才能完成运行。处理可以处理中断。该公司将在接下来的 6 个月内每个周末运行这项工作。哪种 EC2 实例购买选项能够最经济高效地满足这些要求？英文：A company needs to run a batch data-processing job on Amazon EC2 instances. The job will run during the weekend and will take 90 minutes to finish running. The processing can handle interruptions. The company will run the job every weekend for the next 6 months. Which EC2 instance purchasing option will meet these requirements MOST cost-effectively?

ML 工程师在 us-east-1 区域的账户 A 中有一个 Amazon Comprehend 自定义模型。 ML 工程师需要将模型复制到同一区域的 Account B 中。哪种解决方案能够以最少的开发工作满足此要求？英文：An ML engineer has an Amazon Comprehend custom model in Account A in the us-east-1 Region. The ML engineer needs to copy the model to Account В in the same Region. Which solution will meet this requirement with the LEAST development effort ?

机器学习工程师正在训练一个简单的神经网络模型。机器学习工程师在验证数据集上跟踪模型随时间的表现。该模型的性能首先大幅提高，然后在特定数量的 epoch 后下降。哪些解决方案可以缓解这个问题？（选择两个） An ML engineer is training a simple neural network model. The ML engineer tracks the performance of the model over time on a validation dataset. The model's performance improves substantially at first and then degrades after a specific number of epochs. Which solutions will mitigate this problem? (Choose two.)

一家公司有一个检索增强生成 (RAG) 应用程序，该应用程序使用矢量数据库来存储文档的嵌入。该公司必须将应用程序迁移到 AWS，并且必须实施提供文本文件语义搜索的解决方案。该公司已将文本存储库迁移到 Amazon S3 存储桶。哪种解决方案可以满足这些要求？英文：A company has a Retrieval Augmented Generation (RAG) application that uses a vector database to store embeddings of documents. The Company must migrate the application to AWS and must implement a solution that provides semantic search of text files. The company has already migrated the text repository to an Amazon S3 bucket. Which solution will meet these requirements?

一家公司有一个 ML 模型，可以根据客户上传到公司网站的图像生成文本描述。图像的总大小最大可达 50 MB。 ML 工程师决定将图像存储在 Amazon S3 存储桶中。机器学习工程师必须实施一个可以扩展以适应需求变化的处理解决方案。哪种解决方案能够以最少的运营开销满足这些要求？英文：A company has an ML model that generates text descriptions based on images that customers upload to the company's website. The images can be up to 50 MB in total size. An ML engineer decides to store the images in an Amazon S3 bucket. The ML engineer must implement a processing solution that can scale to accommodate changes in demand. Which solution will meet these requirements with the LEAST operational overhead?

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